Top-down approaches to process improvement based on generic "best practice" models (e.g., CMM, TRILLIUM, BOOTSTRAP, SPICE) have become popular. Despite the idiosyncrasies of each of these approaches, they share some common characteristics: all of them are based on numerous assumptions about what are best practices, and about the business goals of organizations and the problems they face. Other organizations, like the Software Engineering Laboratory of the NASA Goddard Space Flight Center, HP and CRIM in Canada, have adopted the Quality Improvement Paradigm (QIP). The QIP stipulates a more bottom-up and inductive approach to process improvement. The focus of this paradigm is to first understand what processes exist in the organization and to determine what causes the most significant problems. Based on this, opportunities for improvement are devised, and empirical studies are conducted to evaluate potential solutions. In this paper, we present a method, named AINSI (An INductive Software process Improvment method), which defines general but concrete steps and guidelines for putting in place the QIP. This method is the result of the collective experiences of the authors and integrates many lessons learned from process improvement efforts in different environments. It also integrates many complementary techniques such as qualitative analysis, methods for data collection (e.g., the Goal/Question/Metric paradigm), and quantitative evaluation. (Also cross-referenced as UMIACS-TR-95-77)